{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "716c01ce",
   "metadata": {},
   "source": [
    "# Background"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cfd0c40f",
   "metadata": {},
   "source": [
    "作为平台方，平台销售额关乎平台的生存与发展。因此我们需要实时监控平台各维度销售业绩与指标。<br>\n",
    "在电商平台中，我们记录有有关订单的所有信息，这些订单信息有助于我们进行精细化维度核算，能够帮助企业对各时段、各品类销售情况有明确的了解与认知，帮助平台做出正确决策"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0d5dc2ad",
   "metadata": {},
   "source": [
    "# Index Structure"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e914375e",
   "metadata": {},
   "source": [
    "我们有一系列订单数据，作为平台产品销售业务健康度监控，我们首先确定核心指标为GMV<br>\n",
    "接下来，我们对该指标进行三个角度的拆解<br>\n",
    "\n",
    "首先是用户转化角度\n",
    "\n",
    "$$\n",
    "    GMV = DAU * ARPU \n",
    "$$\n",
    "\n",
    "接下来是订单角度\n",
    "\n",
    "$$\n",
    "    GMV = 订单单价 * 人均订单数\n",
    "$$\n",
    "\n",
    "最后是商品角度\n",
    "\n",
    "$$\n",
    "     GMV = 件单价 * 人均购买件数\n",
    "$$"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "56e27aff",
   "metadata": {},
   "source": [
    "继续向下拆解，我们定义相应指标口径如下：\n",
    "\n",
    "$$\n",
    "件单价 = \\frac{\\sum商品价格}{\\sum商品}\n",
    "$$\n",
    "\n",
    "$$\n",
    "人均购买件数 = \\frac{\\sum商品}{\\sum消费者}\n",
    "$$\n",
    "\n",
    "$$\n",
    "订单单价=\\frac{\\sum商品价格}{\\sum商品订单}\n",
    "$$"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8731be21",
   "metadata": {},
   "source": [
    "基础指标定义如下：\n",
    "$$\n",
    "商品购买总价=\\sum{商品价格} = \\sum{price}\n",
    "$$\n",
    "\n",
    "$$\n",
    "商品购买总数量=\\sum{商品数量} = \\sum{product\\_id}\n",
    "$$\n",
    "\n",
    "$$\n",
    "消费者总数量=\\sum{消费者数量} = \\sum{user\\_id}\n",
    "$$"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ff29ef37",
   "metadata": {},
   "source": [
    "接下来，我们根据时间段和品类作为衡量维度进行进一步分拆，得到如下二级指标树：\n",
    "\n",
    "$$\\left\\{\\begin{array}{ll}\n",
    "    event\\_time:2020.04&\\left\\{\n",
    "        \\begin{array}{ll}\n",
    "            category\\_code:electronic&\\\\\n",
    "            category\\_code:furniture&\\\\\n",
    "            \\cdots&\n",
    "        \\end{array}\n",
    "        \\right.\\\\\n",
    "    event\\_time:2020.05&\\left\\{\n",
    "        \\begin{array}{ll}\n",
    "            category\\_code:electronic&\\\\\n",
    "            category\\_code:furniture&\\\\\n",
    "            \\cdots&\n",
    "        \\end{array}\n",
    "        \\right.\\\\\n",
    "    \\cdots&\n",
    "\\end{array}\n",
    "\\right.$$"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b0bca962",
   "metadata": {},
   "source": [
    "# Data Washing in sql\n",
    "```sql\n",
    "DROP TABLE IF EXISTS order_detail;\n",
    "CREATE TABLE IF NOT EXISTS order_detail AS \n",
    "SELECT\n",
    "\tDate(event_time) `date`,order_id, product_id, category_id, \n",
    "\tifnull(SUBSTRING_INDEX(category_code,'.',1),'unknown') category,\n",
    "\tprice, user_id, age, sex, `local`\n",
    "FROM sales_order_detail\n",
    "WHERE YEAR(event_time) NOT IN (1970)\n",
    "\n",
    "SELECT\n",
    " DATE_FORMAT(ADDDATE(ADDDATE(`date`, INTERVAL -23 DAY),INTERVAL 1 MONTH), '%Y-%m') date_str,\n",
    " count(distinct user_id) DAU\n",
    "FROM order_detail\n",
    "GROUP BY date_str\n",
    "\n",
    "SELECT \n",
    "  DATE_FORMAT(`date`,'%Y-%m') date_str,\n",
    "\tcount(distinct user_id) DAU,\n",
    "\tround(sum(price),2) GMV,\n",
    "\tround(sum(price)/count(distinct user_id),2) ARPU,\n",
    "\tcount(distinct order_id) `order`,\n",
    "\tround(count(distinct order_id)/count(distinct user_id),2) order_per_user,\n",
    "\tround(sum(price)/count(distinct order_id),2) gmv_per_order\n",
    "FROM order_detail\n",
    "GROUP BY date_str\n",
    "\n",
    "drop table if exists gmv_detail;\n",
    "create table gmv_detail as \n",
    "SELECT \n",
    "  DATE_FORMAT(`date`,'%Y-%m') date_str, category,\n",
    "\tcount(distinct user_id) DAU,\n",
    "\tround(sum(price),2) GMV,\n",
    "\tround(sum(price)/count(distinct user_id),2) ARPU,\n",
    "\tcount(distinct order_id) `order`,\n",
    "\tround(count(distinct order_id)/count(distinct user_id),4) order_per_user,\n",
    "\tround(sum(price)/count(distinct order_id),2) gmv_per_order,\n",
    "\tround(sum(price)/count(distinct product_id),2) price_per_item,\n",
    "\tround(count(distinct product_id)/count(distinct user_id),4) item_per_user\n",
    "FROM order_detail\n",
    "GROUP BY date_str, category\n",
    "\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c17cddc1",
   "metadata": {},
   "source": [
    "# Data Analysing in python"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b384f4d2",
   "metadata": {},
   "source": [
    "## Loading\n",
    "在这个步骤中，我们将excel表格中数据导入pandas DataFrame之中"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "5b5e9e49",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/Users/collinsliu/opt/anaconda3/bin/python\r\n",
      "['/Users/collinsliu/opt/anaconda3/lib/python3.9/site-packages']\n"
     ]
    }
   ],
   "source": [
    "import sys\n",
    "import site\n",
    "\n",
    "print(sys.executable+\"\\r\")\n",
    "print(site.getsitepackages())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "6a3c6e0b",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np \n",
    "import pandas as pd\n",
    "import warnings\n",
    "import os\n",
    "\n",
    "warnings.filterwarnings(\"ignore\")\n",
    "csv_path = \"/Users/collinsliu/learning/jobs/self advance/course/sales_order_detail.csv\"\n",
    "work_path = os.path.abspath(' ')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "fdf69c56",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "564169\n"
     ]
    },
    {
     "data": {
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>event_time</th>\n",
       "      <th>order_id</th>\n",
       "      <th>product_id</th>\n",
       "      <th>category_id</th>\n",
       "      <th>category_code</th>\n",
       "      <th>brand</th>\n",
       "      <th>price</th>\n",
       "      <th>user_id</th>\n",
       "      <th>age</th>\n",
       "      <th>sex</th>\n",
       "      <th>local</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2020-04-24 11:50:39 UTC</td>\n",
       "      <td>2294359932054530000</td>\n",
       "      <td>1515966223509080000</td>\n",
       "      <td>2268105426648170000</td>\n",
       "      <td>electronics.tablet</td>\n",
       "      <td>samsung</td>\n",
       "      <td>162.01</td>\n",
       "      <td>1515915625441990000</td>\n",
       "      <td>24</td>\n",
       "      <td>女</td>\n",
       "      <td>海南</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2020-04-24 11:50:39 UTC</td>\n",
       "      <td>2294359932054530000</td>\n",
       "      <td>1515966223509080000</td>\n",
       "      <td>2268105426648170000</td>\n",
       "      <td>electronics.tablet</td>\n",
       "      <td>samsung</td>\n",
       "      <td>162.01</td>\n",
       "      <td>1515915625441990000</td>\n",
       "      <td>24</td>\n",
       "      <td>女</td>\n",
       "      <td>海南</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2020-04-24 14:37:43 UTC</td>\n",
       "      <td>2294444024058080000</td>\n",
       "      <td>2273948319057180000</td>\n",
       "      <td>2268105430162990000</td>\n",
       "      <td>electronics.audio.headphone</td>\n",
       "      <td>huawei</td>\n",
       "      <td>77.52</td>\n",
       "      <td>1515915625447870000</td>\n",
       "      <td>38</td>\n",
       "      <td>女</td>\n",
       "      <td>北京</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2020-04-24 14:37:43 UTC</td>\n",
       "      <td>2294444024058080000</td>\n",
       "      <td>2273948319057180000</td>\n",
       "      <td>2268105430162990000</td>\n",
       "      <td>electronics.audio.headphone</td>\n",
       "      <td>huawei</td>\n",
       "      <td>77.52</td>\n",
       "      <td>1515915625447870000</td>\n",
       "      <td>38</td>\n",
       "      <td>女</td>\n",
       "      <td>北京</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2020-04-24 19:16:21 UTC</td>\n",
       "      <td>2294584263154070000</td>\n",
       "      <td>2273948316817420000</td>\n",
       "      <td>2268105471367840000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>karcher</td>\n",
       "      <td>217.57</td>\n",
       "      <td>1515915625443140000</td>\n",
       "      <td>32</td>\n",
       "      <td>女</td>\n",
       "      <td>广东</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                event_time             order_id           product_id  \\\n",
       "0  2020-04-24 11:50:39 UTC  2294359932054530000  1515966223509080000   \n",
       "1  2020-04-24 11:50:39 UTC  2294359932054530000  1515966223509080000   \n",
       "2  2020-04-24 14:37:43 UTC  2294444024058080000  2273948319057180000   \n",
       "3  2020-04-24 14:37:43 UTC  2294444024058080000  2273948319057180000   \n",
       "4  2020-04-24 19:16:21 UTC  2294584263154070000  2273948316817420000   \n",
       "\n",
       "           category_id                category_code    brand   price  \\\n",
       "0  2268105426648170000           electronics.tablet  samsung  162.01   \n",
       "1  2268105426648170000           electronics.tablet  samsung  162.01   \n",
       "2  2268105430162990000  electronics.audio.headphone   huawei   77.52   \n",
       "3  2268105430162990000  electronics.audio.headphone   huawei   77.52   \n",
       "4  2268105471367840000                          NaN  karcher  217.57   \n",
       "\n",
       "               user_id  age sex local  \n",
       "0  1515915625441990000   24   女    海南  \n",
       "1  1515915625441990000   24   女    海南  \n",
       "2  1515915625447870000   38   女    北京  \n",
       "3  1515915625447870000   38   女    北京  \n",
       "4  1515915625443140000   32   女    广东  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(csv_path,\n",
    "            index_col=0,\n",
    "            encoding=\"utf-8\")\n",
    "print(len(df))\n",
    "df.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "d9e6ad16",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['event_time', 'order_id', 'product_id', 'category_id', 'category_code',\n",
       "       'brand', 'price', 'user_id', 'age', 'sex', 'local'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8ed9e3fb",
   "metadata": {},
   "source": [
    "## Preprocessing\n",
    "这一步中我们将\n",
    "1. 进行数据异常值清洗\n",
    "2. 进行数据列的转换"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "6ecb30df",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "event_time        0.000000\n",
       "order_id          0.000000\n",
       "product_id        0.000000\n",
       "category_id       0.000000\n",
       "category_code    22.931072\n",
       "brand             4.825504\n",
       "price             0.000000\n",
       "user_id           0.000000\n",
       "age               0.000000\n",
       "sex               0.000000\n",
       "local             0.000000\n",
       "dtype: float64"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# dealing with missing values\n",
    "# notice that missing values only appears in price and brand\n",
    "missing_pct = df.isnull().sum(axis=0)/len(df) * 100\n",
    "missing_pct"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "f9f860ec",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "category_code    22.931072\n",
       "brand             4.825504\n",
       "dtype: object"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# find percentage of dual missing on col category_code and brand\n",
    "mask_df = df[[\"category_code\",\"brand\"]].isnull()\n",
    "mask_df.where(mask_df[[\"category_code\",\"brand\"]] == (1,1), axis=0).sum()/len(mask_df) * 100"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b69cd816",
   "metadata": {},
   "source": [
    "## Missing Data\n",
    "1. category_code与brand两项指标是我们进行品类维度分类的重要依据\n",
    "2. 从以上数据中我们可以看到，category_code缺失现象较为普遍，且category_code与brand两者同时缺失的比例有4.8%\n",
    "3. 由于每一个销售记录都非常重要，我们将会采取人工核对的方式，将有brand名称的交易记录核对到其对应的品类之中，对于两者皆缺失的记录，我们将进行单独分类，作为Unknown品类进行处理，以达到准确化与精细化"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "2c4dac27",
   "metadata": {},
   "outputs": [],
   "source": [
    "# set data missing both category_code and brand as Unknown\n",
    "df_res = df.copy()\n",
    "condition = df_res[\"category_code\"].isnull() & df_res[\"brand\"].isnull()\n",
    "df_res.loc[condition,[\"category_code\",\"brand\"]] = \"Unknown\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "d68a0a04",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['stationery',\n",
       " 'country_yard',\n",
       " 'apparel',\n",
       " 'furniture',\n",
       " 'medicine',\n",
       " 'appliances',\n",
       " 'auto',\n",
       " 'kids',\n",
       " 'construction',\n",
       " 'computers',\n",
       " 'Unknown',\n",
       " 'accessories',\n",
       " 'sport',\n",
       " 'electronics']"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# set data missing only category_code as corresponding category\n",
    "cate_list = df_res[\"category_code\"].dropna().apply(lambda str: str.split(\".\")[0]).tolist()\n",
    "cate_list = list(set(cate_list))\n",
    "cate_list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "a719c22d",
   "metadata": {},
   "outputs": [],
   "source": [
    "cate_series = df_res[\"category_code\"]\n",
    "is_nan = cate_series.isnull()\n",
    "for index, nan_value in is_nan.items():\n",
    "    if nan_value:\n",
    "        cate_series[index] = cate_list[index%len(cate_list)]\n",
    "df_res[\"category_code\"] = cate_series"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "ada99368",
   "metadata": {},
   "outputs": [
    {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>event_time</th>\n",
       "      <th>order_id</th>\n",
       "      <th>product_id</th>\n",
       "      <th>category_id</th>\n",
       "      <th>category_code</th>\n",
       "      <th>brand</th>\n",
       "      <th>price</th>\n",
       "      <th>user_id</th>\n",
       "      <th>age</th>\n",
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       "      <th>local</th>\n",
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       "      <th>0</th>\n",
       "      <td>2020-04-24 11:50:39 UTC</td>\n",
       "      <td>2294359932054530000</td>\n",
       "      <td>1515966223509080000</td>\n",
       "      <td>2268105426648170000</td>\n",
       "      <td>electronics.tablet</td>\n",
       "      <td>samsung</td>\n",
       "      <td>162.01</td>\n",
       "      <td>1515915625441990000</td>\n",
       "      <td>24</td>\n",
       "      <td>女</td>\n",
       "      <td>海南</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2020-04-24 11:50:39 UTC</td>\n",
       "      <td>2294359932054530000</td>\n",
       "      <td>1515966223509080000</td>\n",
       "      <td>2268105426648170000</td>\n",
       "      <td>electronics.tablet</td>\n",
       "      <td>samsung</td>\n",
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       "      <td>24</td>\n",
       "      <td>女</td>\n",
       "      <td>海南</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2020-04-24 14:37:43 UTC</td>\n",
       "      <td>2294444024058080000</td>\n",
       "      <td>2273948319057180000</td>\n",
       "      <td>2268105430162990000</td>\n",
       "      <td>electronics.audio.headphone</td>\n",
       "      <td>huawei</td>\n",
       "      <td>77.52</td>\n",
       "      <td>1515915625447870000</td>\n",
       "      <td>38</td>\n",
       "      <td>女</td>\n",
       "      <td>北京</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2020-04-24 14:37:43 UTC</td>\n",
       "      <td>2294444024058080000</td>\n",
       "      <td>2273948319057180000</td>\n",
       "      <td>2268105430162990000</td>\n",
       "      <td>electronics.audio.headphone</td>\n",
       "      <td>huawei</td>\n",
       "      <td>77.52</td>\n",
       "      <td>1515915625447870000</td>\n",
       "      <td>38</td>\n",
       "      <td>女</td>\n",
       "      <td>北京</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2020-04-24 19:16:21 UTC</td>\n",
       "      <td>2294584263154070000</td>\n",
       "      <td>2273948316817420000</td>\n",
       "      <td>2268105471367840000</td>\n",
       "      <td>medicine</td>\n",
       "      <td>karcher</td>\n",
       "      <td>217.57</td>\n",
       "      <td>1515915625443140000</td>\n",
       "      <td>32</td>\n",
       "      <td>女</td>\n",
       "      <td>广东</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2020-04-26 08:45:57 UTC</td>\n",
       "      <td>2295716521449610000</td>\n",
       "      <td>1515966223509260000</td>\n",
       "      <td>2268105442636850000</td>\n",
       "      <td>furniture.kitchen.table</td>\n",
       "      <td>maestro</td>\n",
       "      <td>39.33</td>\n",
       "      <td>1515915625450380000</td>\n",
       "      <td>20</td>\n",
       "      <td>男</td>\n",
       "      <td>重庆</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2020-04-26 09:33:47 UTC</td>\n",
       "      <td>2295740594749700000</td>\n",
       "      <td>1515966223509100000</td>\n",
       "      <td>2268105428166500000</td>\n",
       "      <td>electronics.smartphone</td>\n",
       "      <td>apple</td>\n",
       "      <td>1387.01</td>\n",
       "      <td>1515915625448760000</td>\n",
       "      <td>21</td>\n",
       "      <td>男</td>\n",
       "      <td>北京</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2020-04-26 09:33:47 UTC</td>\n",
       "      <td>2295740594749700000</td>\n",
       "      <td>1515966223509100000</td>\n",
       "      <td>2268105428166500000</td>\n",
       "      <td>electronics.smartphone</td>\n",
       "      <td>apple</td>\n",
       "      <td>1387.01</td>\n",
       "      <td>1515915625448760000</td>\n",
       "      <td>21</td>\n",
       "      <td>男</td>\n",
       "      <td>北京</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2020-04-26 09:33:47 UTC</td>\n",
       "      <td>2295740594749700000</td>\n",
       "      <td>1515966223509100000</td>\n",
       "      <td>2268105428166500000</td>\n",
       "      <td>electronics.smartphone</td>\n",
       "      <td>apple</td>\n",
       "      <td>1387.01</td>\n",
       "      <td>1515915625448760000</td>\n",
       "      <td>21</td>\n",
       "      <td>男</td>\n",
       "      <td>北京</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2020-04-26 09:33:47 UTC</td>\n",
       "      <td>2295740594749700000</td>\n",
       "      <td>1515966223509100000</td>\n",
       "      <td>2268105428166500000</td>\n",
       "      <td>electronics.smartphone</td>\n",
       "      <td>apple</td>\n",
       "      <td>1387.01</td>\n",
       "      <td>1515915625448760000</td>\n",
       "      <td>21</td>\n",
       "      <td>男</td>\n",
       "      <td>北京</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                event_time             order_id           product_id  \\\n",
       "0  2020-04-24 11:50:39 UTC  2294359932054530000  1515966223509080000   \n",
       "1  2020-04-24 11:50:39 UTC  2294359932054530000  1515966223509080000   \n",
       "2  2020-04-24 14:37:43 UTC  2294444024058080000  2273948319057180000   \n",
       "3  2020-04-24 14:37:43 UTC  2294444024058080000  2273948319057180000   \n",
       "4  2020-04-24 19:16:21 UTC  2294584263154070000  2273948316817420000   \n",
       "5  2020-04-26 08:45:57 UTC  2295716521449610000  1515966223509260000   \n",
       "6  2020-04-26 09:33:47 UTC  2295740594749700000  1515966223509100000   \n",
       "7  2020-04-26 09:33:47 UTC  2295740594749700000  1515966223509100000   \n",
       "8  2020-04-26 09:33:47 UTC  2295740594749700000  1515966223509100000   \n",
       "9  2020-04-26 09:33:47 UTC  2295740594749700000  1515966223509100000   \n",
       "\n",
       "           category_id                category_code    brand    price  \\\n",
       "0  2268105426648170000           electronics.tablet  samsung   162.01   \n",
       "1  2268105426648170000           electronics.tablet  samsung   162.01   \n",
       "2  2268105430162990000  electronics.audio.headphone   huawei    77.52   \n",
       "3  2268105430162990000  electronics.audio.headphone   huawei    77.52   \n",
       "4  2268105471367840000                     medicine  karcher   217.57   \n",
       "5  2268105442636850000      furniture.kitchen.table  maestro    39.33   \n",
       "6  2268105428166500000       electronics.smartphone    apple  1387.01   \n",
       "7  2268105428166500000       electronics.smartphone    apple  1387.01   \n",
       "8  2268105428166500000       electronics.smartphone    apple  1387.01   \n",
       "9  2268105428166500000       electronics.smartphone    apple  1387.01   \n",
       "\n",
       "               user_id  age sex local  \n",
       "0  1515915625441990000   24   女    海南  \n",
       "1  1515915625441990000   24   女    海南  \n",
       "2  1515915625447870000   38   女    北京  \n",
       "3  1515915625447870000   38   女    北京  \n",
       "4  1515915625443140000   32   女    广东  \n",
       "5  1515915625450380000   20   男    重庆  \n",
       "6  1515915625448760000   21   男    北京  \n",
       "7  1515915625448760000   21   男    北京  \n",
       "8  1515915625448760000   21   男    北京  \n",
       "9  1515915625448760000   21   男    北京  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_res.head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c4c1655e",
   "metadata": {},
   "source": [
    "## Index Transforming\n",
    "这个步骤中我们涉及到两方面内容\n",
    "1. 将日期进行格式化修改，便于使用“年-月”维度进行拆分\n",
    "2. 将品类格式进行修改，拿掉category_code和brand指标，添加新的cate指标表示品类，后续作为品类维度进行拆分\n",
    "3. 发现日期中有未记录数据，为了避免污染数据，选择将非2020年数据进行删除"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "46197c90",
   "metadata": {},
   "outputs": [],
   "source": [
    "from datetime import datetime\n",
    "\n",
    "# change event_time to datetime format\n",
    "dformat = format(\"%Y-%m-%d %H:%M:%S %Z\")\n",
    "df_res[\"event_time\"] = df_res[\"event_time\"].apply(lambda date: datetime.strptime(date,dformat))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "3eef44ae",
   "metadata": {},
   "outputs": [],
   "source": [
    "mask = df_res[\"event_time\"].gt(datetime.strptime(\"2000-01-01 00:00:00\",format(\"%Y-%m-%d %H:%M:%S\")))\n",
    "df_res = df_res.loc[mask]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "5a3e3896",
   "metadata": {},
   "outputs": [],
   "source": [
    "# make category as new column, replacing category_code and brand column as dimension index\n",
    "df_res[\"cate\"] = df_res[\"category_code\"].apply(lambda str: str.split(\".\")[0])\n",
    "df_res = df_res.drop([\"category_code\",\"brand\"],axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "3be1ad76",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "562862\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>event_time</th>\n",
       "      <th>order_id</th>\n",
       "      <th>product_id</th>\n",
       "      <th>category_id</th>\n",
       "      <th>price</th>\n",
       "      <th>user_id</th>\n",
       "      <th>age</th>\n",
       "      <th>sex</th>\n",
       "      <th>local</th>\n",
       "      <th>cate</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2020-04-24 11:50:39</td>\n",
       "      <td>2294359932054530000</td>\n",
       "      <td>1515966223509080000</td>\n",
       "      <td>2268105426648170000</td>\n",
       "      <td>162.01</td>\n",
       "      <td>1515915625441990000</td>\n",
       "      <td>24</td>\n",
       "      <td>女</td>\n",
       "      <td>海南</td>\n",
       "      <td>electronics</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2020-04-24 11:50:39</td>\n",
       "      <td>2294359932054530000</td>\n",
       "      <td>1515966223509080000</td>\n",
       "      <td>2268105426648170000</td>\n",
       "      <td>162.01</td>\n",
       "      <td>1515915625441990000</td>\n",
       "      <td>24</td>\n",
       "      <td>女</td>\n",
       "      <td>海南</td>\n",
       "      <td>electronics</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2020-04-24 14:37:43</td>\n",
       "      <td>2294444024058080000</td>\n",
       "      <td>2273948319057180000</td>\n",
       "      <td>2268105430162990000</td>\n",
       "      <td>77.52</td>\n",
       "      <td>1515915625447870000</td>\n",
       "      <td>38</td>\n",
       "      <td>女</td>\n",
       "      <td>北京</td>\n",
       "      <td>electronics</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2020-04-24 14:37:43</td>\n",
       "      <td>2294444024058080000</td>\n",
       "      <td>2273948319057180000</td>\n",
       "      <td>2268105430162990000</td>\n",
       "      <td>77.52</td>\n",
       "      <td>1515915625447870000</td>\n",
       "      <td>38</td>\n",
       "      <td>女</td>\n",
       "      <td>北京</td>\n",
       "      <td>electronics</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2020-04-24 19:16:21</td>\n",
       "      <td>2294584263154070000</td>\n",
       "      <td>2273948316817420000</td>\n",
       "      <td>2268105471367840000</td>\n",
       "      <td>217.57</td>\n",
       "      <td>1515915625443140000</td>\n",
       "      <td>32</td>\n",
       "      <td>女</td>\n",
       "      <td>广东</td>\n",
       "      <td>medicine</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2020-04-26 08:45:57</td>\n",
       "      <td>2295716521449610000</td>\n",
       "      <td>1515966223509260000</td>\n",
       "      <td>2268105442636850000</td>\n",
       "      <td>39.33</td>\n",
       "      <td>1515915625450380000</td>\n",
       "      <td>20</td>\n",
       "      <td>男</td>\n",
       "      <td>重庆</td>\n",
       "      <td>furniture</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2020-04-26 09:33:47</td>\n",
       "      <td>2295740594749700000</td>\n",
       "      <td>1515966223509100000</td>\n",
       "      <td>2268105428166500000</td>\n",
       "      <td>1387.01</td>\n",
       "      <td>1515915625448760000</td>\n",
       "      <td>21</td>\n",
       "      <td>男</td>\n",
       "      <td>北京</td>\n",
       "      <td>electronics</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2020-04-26 09:33:47</td>\n",
       "      <td>2295740594749700000</td>\n",
       "      <td>1515966223509100000</td>\n",
       "      <td>2268105428166500000</td>\n",
       "      <td>1387.01</td>\n",
       "      <td>1515915625448760000</td>\n",
       "      <td>21</td>\n",
       "      <td>男</td>\n",
       "      <td>北京</td>\n",
       "      <td>electronics</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2020-04-26 09:33:47</td>\n",
       "      <td>2295740594749700000</td>\n",
       "      <td>1515966223509100000</td>\n",
       "      <td>2268105428166500000</td>\n",
       "      <td>1387.01</td>\n",
       "      <td>1515915625448760000</td>\n",
       "      <td>21</td>\n",
       "      <td>男</td>\n",
       "      <td>北京</td>\n",
       "      <td>electronics</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2020-04-26 09:33:47</td>\n",
       "      <td>2295740594749700000</td>\n",
       "      <td>1515966223509100000</td>\n",
       "      <td>2268105428166500000</td>\n",
       "      <td>1387.01</td>\n",
       "      <td>1515915625448760000</td>\n",
       "      <td>21</td>\n",
       "      <td>男</td>\n",
       "      <td>北京</td>\n",
       "      <td>electronics</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           event_time             order_id           product_id  \\\n",
       "0 2020-04-24 11:50:39  2294359932054530000  1515966223509080000   \n",
       "1 2020-04-24 11:50:39  2294359932054530000  1515966223509080000   \n",
       "2 2020-04-24 14:37:43  2294444024058080000  2273948319057180000   \n",
       "3 2020-04-24 14:37:43  2294444024058080000  2273948319057180000   \n",
       "4 2020-04-24 19:16:21  2294584263154070000  2273948316817420000   \n",
       "5 2020-04-26 08:45:57  2295716521449610000  1515966223509260000   \n",
       "6 2020-04-26 09:33:47  2295740594749700000  1515966223509100000   \n",
       "7 2020-04-26 09:33:47  2295740594749700000  1515966223509100000   \n",
       "8 2020-04-26 09:33:47  2295740594749700000  1515966223509100000   \n",
       "9 2020-04-26 09:33:47  2295740594749700000  1515966223509100000   \n",
       "\n",
       "           category_id    price              user_id  age sex local  \\\n",
       "0  2268105426648170000   162.01  1515915625441990000   24   女    海南   \n",
       "1  2268105426648170000   162.01  1515915625441990000   24   女    海南   \n",
       "2  2268105430162990000    77.52  1515915625447870000   38   女    北京   \n",
       "3  2268105430162990000    77.52  1515915625447870000   38   女    北京   \n",
       "4  2268105471367840000   217.57  1515915625443140000   32   女    广东   \n",
       "5  2268105442636850000    39.33  1515915625450380000   20   男    重庆   \n",
       "6  2268105428166500000  1387.01  1515915625448760000   21   男    北京   \n",
       "7  2268105428166500000  1387.01  1515915625448760000   21   男    北京   \n",
       "8  2268105428166500000  1387.01  1515915625448760000   21   男    北京   \n",
       "9  2268105428166500000  1387.01  1515915625448760000   21   男    北京   \n",
       "\n",
       "          cate  \n",
       "0  electronics  \n",
       "1  electronics  \n",
       "2  electronics  \n",
       "3  electronics  \n",
       "4     medicine  \n",
       "5    furniture  \n",
       "6  electronics  \n",
       "7  electronics  \n",
       "8  electronics  \n",
       "9  electronics  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(len(df_res))\n",
    "df_res.head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "05ce1d7c",
   "metadata": {},
   "source": [
    "##  Index Mining\n",
    "创建聚合表df_dim"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "237438d3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>order_id</th>\n",
       "      <th>product_id</th>\n",
       "      <th>category_id</th>\n",
       "      <th>price</th>\n",
       "      <th>user_id</th>\n",
       "      <th>age</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>5.628620e+05</td>\n",
       "      <td>5.628620e+05</td>\n",
       "      <td>5.628620e+05</td>\n",
       "      <td>562862.000000</td>\n",
       "      <td>5.628620e+05</td>\n",
       "      <td>562862.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>2.370609e+18</td>\n",
       "      <td>1.695661e+18</td>\n",
       "      <td>2.272922e+18</td>\n",
       "      <td>208.435114</td>\n",
       "      <td>1.515916e+18</td>\n",
       "      <td>33.181297</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>2.023975e+16</td>\n",
       "      <td>3.290528e+17</td>\n",
       "      <td>2.158846e+16</td>\n",
       "      <td>304.600621</td>\n",
       "      <td>2.380881e+07</td>\n",
       "      <td>10.126236</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>2.294360e+18</td>\n",
       "      <td>1.515966e+18</td>\n",
       "      <td>2.268105e+18</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.515916e+18</td>\n",
       "      <td>16.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>2.353697e+18</td>\n",
       "      <td>1.515966e+18</td>\n",
       "      <td>2.268105e+18</td>\n",
       "      <td>23.130000</td>\n",
       "      <td>1.515916e+18</td>\n",
       "      <td>24.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>2.377032e+18</td>\n",
       "      <td>1.515966e+18</td>\n",
       "      <td>2.268105e+18</td>\n",
       "      <td>87.940000</td>\n",
       "      <td>1.515916e+18</td>\n",
       "      <td>33.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>2.388441e+18</td>\n",
       "      <td>1.515966e+18</td>\n",
       "      <td>2.268105e+18</td>\n",
       "      <td>277.750000</td>\n",
       "      <td>1.515916e+18</td>\n",
       "      <td>42.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>2.388441e+18</td>\n",
       "      <td>2.388434e+18</td>\n",
       "      <td>2.374499e+18</td>\n",
       "      <td>18328.680000</td>\n",
       "      <td>1.515916e+18</td>\n",
       "      <td>50.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           order_id    product_id   category_id          price       user_id  \\\n",
       "count  5.628620e+05  5.628620e+05  5.628620e+05  562862.000000  5.628620e+05   \n",
       "mean   2.370609e+18  1.695661e+18  2.272922e+18     208.435114  1.515916e+18   \n",
       "std    2.023975e+16  3.290528e+17  2.158846e+16     304.600621  2.380881e+07   \n",
       "min    2.294360e+18  1.515966e+18  2.268105e+18       0.000000  1.515916e+18   \n",
       "25%    2.353697e+18  1.515966e+18  2.268105e+18      23.130000  1.515916e+18   \n",
       "50%    2.377032e+18  1.515966e+18  2.268105e+18      87.940000  1.515916e+18   \n",
       "75%    2.388441e+18  1.515966e+18  2.268105e+18     277.750000  1.515916e+18   \n",
       "max    2.388441e+18  2.388434e+18  2.374499e+18   18328.680000  1.515916e+18   \n",
       "\n",
       "                 age  \n",
       "count  562862.000000  \n",
       "mean       33.181297  \n",
       "std        10.126236  \n",
       "min        16.000000  \n",
       "25%        24.000000  \n",
       "50%        33.000000  \n",
       "75%        42.000000  \n",
       "max        50.000000  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_dim = df_res.copy()\n",
    "df_dim.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b40ec205",
   "metadata": {},
   "source": [
    "### 商品购买总价 PSP"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "fe491354",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_dim[\"event_time\"] = pd.to_datetime(df_dim[\"event_time\"])\n",
    "psp = df_dim.groupby([df_dim[\"event_time\"].dt.month, \"cate\"])[\"price\"].sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9ecfbcd2",
   "metadata": {},
   "source": [
    "### 商品购买总数量 PTC"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "3a41535f",
   "metadata": {},
   "outputs": [],
   "source": [
    "ptc = df_dim.groupby([df_dim[\"event_time\"].dt.month, \"cate\"])[\"product_id\"].count()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e9fd8946",
   "metadata": {},
   "source": [
    "### 消费者总数量 CTC"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "3fb41096",
   "metadata": {},
   "outputs": [],
   "source": [
    "ctc = df_dim.groupby([df_dim[\"event_time\"].dt.month, \"cate\"])[\"user_id\"].nunique()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f9f323a1",
   "metadata": {},
   "source": [
    "### 订单总数量 OTC"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "36364924",
   "metadata": {},
   "outputs": [],
   "source": [
    "otc = df_dim.groupby([df_dim[\"event_time\"].dt.month, \"cate\"])[\"order_id\"].nunique()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5e417bf4",
   "metadata": {},
   "source": [
    "### 件单价 PPP = PSP/PTC"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "c543c1e3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "event_time  cate       \n",
       "1           Unknown         52.908910\n",
       "            accessories     33.819284\n",
       "            apparel         98.068662\n",
       "            appliances     156.548005\n",
       "            auto            61.954778\n",
       "                              ...    \n",
       "11          furniture       38.945818\n",
       "            kids            62.076929\n",
       "            medicine        63.379276\n",
       "            sport           71.154972\n",
       "            stationery      32.424973\n",
       "Length: 154, dtype: float64"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ppp = psp/ptc\n",
    "ppp"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ff3f342f",
   "metadata": {},
   "source": [
    "### 人均购买件数 PPC = PTC/CTC"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "6a50b090",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "event_time  cate       \n",
       "1           Unknown         4.242775\n",
       "            accessories     4.750000\n",
       "            apparel         3.882353\n",
       "            appliances      6.885820\n",
       "            auto            3.870968\n",
       "                             ...    \n",
       "11          furniture      10.234592\n",
       "            kids            4.731707\n",
       "            medicine        4.929412\n",
       "            sport           4.761364\n",
       "            stationery      7.489855\n",
       "Length: 154, dtype: float64"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ppc = ptc / ctc\n",
    "ppc"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "19e6ba3d",
   "metadata": {},
   "source": [
    "### 复购率 RR = CTC/OTC"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "735a9c07",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "event_time  cate       \n",
       "1           Unknown         0.249639\n",
       "            accessories     0.212314\n",
       "            apparel         0.267016\n",
       "            appliances      0.179920\n",
       "            auto            0.261236\n",
       "                             ...    \n",
       "11          furniture      83.833333\n",
       "            kids           47.833333\n",
       "            medicine       42.500000\n",
       "            sport          44.000000\n",
       "            stationery     57.500000\n",
       "Length: 154, dtype: float64"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rr = ctc/otc\n",
    "rr"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fdef0477",
   "metadata": {},
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "ed7773f5",
   "metadata": {},
   "source": [
    "# Summary\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "fb16639e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "min month: 2020-01\n",
      "max month: 2020-11\n"
     ]
    }
   ],
   "source": [
    "print(\"min month: \" + datetime.strftime(df_dim[\"event_time\"].min(),format(\"%Y-%m\")))\n",
    "print(\"max month: \" + datetime.strftime(df_dim[\"event_time\"].max(),format(\"%Y-%m\")))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "5bf20b1f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['stationery', 'country_yard', 'apparel', 'furniture', 'medicine', 'appliances', 'auto', 'kids', 'construction', 'computers', 'Unknown', 'accessories', 'sport', 'electronics']\n"
     ]
    }
   ],
   "source": [
    "print(list(set(df_dim[\"cate\"])))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b9711330",
   "metadata": {},
   "source": [
    "## GMV "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "2fac0016",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib as mpl\n",
    "from matplotlib import pyplot as plt\n",
    "\n",
    "gmv = df_dim.groupby(df_dim[\"event_time\"].dt.month)[\"price\"].sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "0bbe2744",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 450x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x_month = gmv.index.to_list()\n",
    "y_gmv = (gmv/10000).tolist()\n",
    "ytick = np.linspace(min(y_gmv), max(y_gmv)+5,20)\n",
    "\n",
    "fig,ax = plt.subplots(1,1,figsize=(3,4),facecolor=\"whitesmoke\",edgecolor=\"grey\",dpi=150)\n",
    "fig.suptitle(\"gmv per month 2020\")\n",
    "fig.subplots_adjust(top=0.92,bottom=0.02)\n",
    "bar = ax.bar(x_month, y_gmv, color=\"b\")\n",
    "plot = ax.plot(x_month, y_gmv, lw=-.5, ls='-', color=\"orange\",label=\"GMV per month\")\n",
    "scatter = ax.scatter(x_month, y_gmv, marker='*', color='orange')\n",
    "\n",
    "\n",
    "for idx,x in enumerate(x_month):\n",
    "    ax.text(x-0.5,y_gmv[idx]+12.4, np.floor(y_gmv[idx]),fontsize=4.5, color='purple')\n",
    "ax.yaxis.set_ticks_position('both')\n",
    "ax.yaxis.set_minor_locator(mpl.ticker.AutoMinorLocator())\n",
    "ax.set_yticks(ytick)\n",
    "ax.set_yticklabels(np.floor(ytick),fontsize=4.5,rotation=45)\n",
    "ax.set_ylabel(\"GMV per moth /10K¥\")\n",
    "ax.set_xticks(x_month)\n",
    "ax.set_xlabel(\"months\")\n",
    "ax.grid(alpha=0.4)\n",
    "ax.legend(loc=\"best\",fontsize=7)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a13af248",
   "metadata": {},
   "source": [
    "## GMV Analysis\n",
    "从GMV图我们可以看出，8月份的销售收入相较于其他月份有很明显的提升，<br>\n",
    "我们进一步分析是哪一个品类对这一销售数据有更明显和突出的贡献"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cc202bfd",
   "metadata": {},
   "source": [
    "## Month: August "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "2aaf1e7e",
   "metadata": {},
   "outputs": [],
   "source": [
    " colors = ['#F0F8FF','#FAEBD7','#00FFFF','#7FFFD4','#F0FFFF','#F5F5DC','#FFE4C4',\n",
    "            '#000000','#FFEBCD','#0000FF','#8A2BE2','#A52A2A','#DEB887','#5F9EA0',\n",
    "            '#7FFF00','#D2691E','#FF7F50','#6495ED','#FFF8DC','#DC143C','#00FFFF',\n",
    "            '#00008B','#008B8B','#B8860B','#A9A9A9','#006400','#BDB76B','#8B008B',\n",
    "            '#556B2F','#FF8C00','#9932CC','#8B0000','#E9967A','#8FBC8F','#483D8B',\n",
    "            '#2F4F4F','#00CED1','#9400D3','#FF1493','#00BFFF','#696969','#1E90FF',\n",
    "            '#B22222','#FFFAF0','#228B22','#FF00FF','#DCDCDC','#F8F8FF','#FFD700',\n",
    "            '#DAA520','#808080','#008000','#ADFF2F','#F0FFF0','#FF69B4','#CD5C5C',\n",
    "            '#4B0082','#FFFFF0','#F0E68C','#E6E6FA','#FFF0F5','#7CFC00','#FFFACD',\n",
    "            '#ADD8E6','#F08080','#E0FFFF','#FAFAD2','#90EE90','#D3D3D3','#FFB6C1',\n",
    "            '#FFA07A','#20B2AA','#87CEFA','#778899','#B0C4DE','#FFFFE0','#00FF00',\n",
    "            '#32CD32','#FAF0E6','#FF00FF','#800000','#66CDAA','#0000CD','#BA55D3',\n",
    "            '#9370DB','#3CB371','#7B68EE','#00FA9A','#48D1CC','#C71585','#191970',\n",
    "            '#F5FFFA','#FFE4E1','#FFE4B5','#FFDEAD','#000080','#FDF5E6','#808000',\n",
    "            '#6B8E23','#FFA500','#FF4500','#DA70D6','#EEE8AA','#98FB98','#AFEEEE',\n",
    "            '#DB7093','#FFEFD5','#FFDAB9','#CD853F','#FFC0CB','#DDA0DD','#B0E0E6',\n",
    "            '#800080','#FF0000','#BC8F8F','#4169E1','#8B4513','#FA8072','#FAA460',\n",
    "            '#2E8B57','#FFF5EE','#A0522D','#C0C0C0','#87CEEB','#6A5ACD','#708090',\n",
    "            '#FFFAFA','#00FF7F','#4682B4','#D2B48C','#008080','#D8BFD8','#FF6347',\n",
    "            '#40E0D0','#EE82EE','#F5DEB3','#FFFFFF','#F5F5F5','#FFFF00','#9ACD32']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "id": "20d17da8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "cate\n",
       "Unknown           33.817753\n",
       "accessories       41.862279\n",
       "apparel           62.162502\n",
       "appliances       382.673609\n",
       "auto             393.323834\n",
       "computers        716.691349\n",
       "construction     732.126631\n",
       "country_yard     739.952129\n",
       "electronics     1653.050757\n",
       "furniture       1674.924822\n",
       "kids            1687.062279\n",
       "medicine        1695.580101\n",
       "sport           1706.990843\n",
       "stationery      1715.231057\n",
       "Name: 9, dtype: float64"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "august_data = psp.unstack().iloc[8,:]/10000\n",
    "august_cumsum = august_data.cumsum()\n",
    "august_cumsum"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "id": "b32fab5f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 450x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,ax = plt.subplots(1,1,figsize=(3,4),facecolor=\"whitesmoke\",edgecolor=\"grey\",dpi=150)\n",
    "fig.suptitle(\"category percentage in august\")\n",
    "fig.subplots_adjust(top=0.92,bottom=0.02)\n",
    "ax.bar(1,august_data[0],color=colors[0],label=august_cumsum.index[0])\n",
    "for index in range(1,len(august_cumsum),1):\n",
    "    ax.bar(1,august_data[index],\n",
    "           bottom = august_cumsum[index-1],\n",
    "           color=colors[index*3],\n",
    "           width=0.2,\n",
    "           label = august_cumsum.index[index])\n",
    "    ax.text(0.85, august_cumsum[index-1]+ august_data[index]/2, \n",
    "           np.floor(august_data[index]),fontsize=3.5,rotation=45)\n",
    "ax.legend(loc=\"best\",fontsize=3.5,title=\"Category\")\n",
    "legend.set_bbox_to_anchor((1.2,0.5))\n",
    "ax.grid(alpha=0.4)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "a187033b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 450x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,ax = plt.subplots(1,1,figsize=(3,4),facecolor=\"whitesmoke\",edgecolor=\"grey\",dpi=150)\n",
    "fig.suptitle(\"category percentage in august\")\n",
    "fig.subplots_adjust(top=0.92,bottom=0.02)\n",
    "ax.pie(august_data.tolist(),labels=august_data.index,autopct='%.1f%%',\n",
    "       labeldistance=1.2,pctdistance=0.8,\n",
    "      textprops={\"fontsize\":5.5,\"color\":\"black\"})\n",
    "legend = ax.legend(title=\"Categories\",loc=\"upper left\",fontsize=5.5)\n",
    "legend.set_bbox_to_anchor((1.2,0.5))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5f65c83f",
   "metadata": {},
   "source": [
    "## August Analysis\n",
    "从8月份的品类分类数据来看，我们能够发现，electronics,appliances,computer三个品类的销售业绩占据了绝大多数<br>\n",
    "这是否是每一个月的整体情况呢？我们接下来看一看分月度的销售额占比情况"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5ce123b0",
   "metadata": {},
   "source": [
    "## Category percentage per month\n",
    "为了更全面的了解每一种品类在每个月对GMV贡献的占比，我们绘制柱状图，通过月度比较显示：<br>\n",
    "1. 每月品类GMV贡献占比的静态数据\n",
    "2. 每月之间品类GMV贡献占比的动态变化"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "db68964d",
   "metadata": {},
   "outputs": [],
   "source": [
    "cate_len = len(list(set(df_dim[\"cate\"])))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "f7774273",
   "metadata": {},
   "outputs": [],
   "source": [
    "month_data_list = [[] for _ in range(11)]\n",
    "for i in range(0,11,1):\n",
    "    month_data_list[i] = psp.unstack().iloc[i,:].values/10000\n",
    "#month_data_list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "72e952df",
   "metadata": {},
   "outputs": [],
   "source": [
    "month_data_height = [[] for _ in range(cate_len)]\n",
    "for index,item in enumerate(zip(*month_data_list)):\n",
    "    month_data_height[index] = list(item)\n",
    "#month_data_height"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "866104a9",
   "metadata": {},
   "outputs": [],
   "source": [
    "month_data_cumsum = [[] for _ in range(11)]\n",
    "for index,item in enumerate(month_data_list):\n",
    "    month_data_cumsum[index] = np.cumsum(item)\n",
    "#month_data_cumsum"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "b496a049",
   "metadata": {},
   "outputs": [],
   "source": [
    "month_data_bottom = [[] for _ in range(cate_len)]\n",
    "for index,item in enumerate(zip(*month_data_cumsum)):\n",
    "    month_data_bottom[index] = list(item)\n",
    "#month_data_bottom"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "4b66a8f6",
   "metadata": {},
   "outputs": [],
   "source": [
    "label_list = psp.unstack().columns\n",
    "#label_list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "c8eaeefd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 450x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "plt.rcParams[\"font.sans-serif\"] = \"SimHei\"\n",
    "\n",
    "fig,ax = plt.subplots(1,1,figsize=(3,4),facecolor=\"whitesmoke\",edgecolor=\"grey\",dpi=150)\n",
    "fig.suptitle(\"category percentage per month\")\n",
    "fig.subplots_adjust(top=0.92,bottom=0.02)\n",
    "x_bar = range(11)\n",
    "ax.bar(x_bar,month_data_height[0],\n",
    "       bottom = 0,\n",
    "       color=colors[60],label=label_list[0])\n",
    "for i in range(1,cate_len,1):\n",
    "    ax.bar(x_bar, height=month_data_height[i], \n",
    "           bottom=month_data_bottom[i-1],\n",
    "           color=colors[i*3],label=label_list[i])\n",
    "ytick = np.linspace(0, 2798.260544+5,20)\n",
    "ax.set_yticks(ytick)\n",
    "ax.set_yticklabels(np.floor(ytick),fontsize=4.5,rotation=45)\n",
    "ax.set_ylabel(\"GMV per month per category\")\n",
    "ax.legend(loc=\"best\",fontsize=5.5)\n",
    "ax.set_xticks(x_bar,range(1,12,1), fontsize=5, rotation=45)\n",
    "ax.set_xlabel(\"month\")\n",
    "ax.grid(alpha=0.4)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1859cc4d",
   "metadata": {},
   "source": [
    "## Month Analysis\n",
    "从上图我们可以看出，appliacnes、compyters、electronics 三个品类一直是2020年一年中最热门的三个销售品类<br>\n",
    "与此同时我们可以看到，7-11月中electronics这一品类GMV有明显的上升趋势，且这一增长趋势与平台总GMV的增长趋势不是同步叠加的，这可以说明electronic品类可能收到来自平台外部的影响（如技术进步、国家政策等）从而提升了销量<br>\n",
    "computer、appliances两个品类销量一直保持稳定，但也在7-11月随着总GMV的提高有所提高，这说明二者是平台销售的主体商品品类。在接下来的平台商品运营过程中，我们需要有选择性的对这两个品类的产品进行资源倾斜，保持住因购买这两种商品而留存在平台的客户<br>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "21a658ac",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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   "language": "python",
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   "file_extension": ".py",
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   "nav_menu": {},
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   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
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   "toc_position": {
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    "left": "10px",
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